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shifting specific column to before/after specific column in dataframe

Creating new columns by iterating over rows in pandas dataframeReplacing column values in PandasHow can I fill NaN values in a pandas data frame?Imputation of missing values and dealing with categorical valueshow many rows have values from the same columns pandasHow to use LSTM to make prediction with both feature from the past and the current ones?Resampling pandas Dataframe keeping other columnsPandas Conditional Fill NaN Forward/BackwardHow can I merge 2+ DataFrame objects without duplicating column names?Merging dataframes in Pandas is taking a surprisingly long time

0

$begingroup$

In dataframe example :

 medcine_preg_oth medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3
0 Berplex Berplex None None
1 NaN NaN NaN NaN
2 NaN NaN NaN NaN
3 obmin obmin None None
4 NaN NaN NaN NaN

'medcine_preg_oth1' 'medcine_preg_oth2' 'medcine_preg_oth3' ,these three columns are in somewhere of dataframe with other columns.

I want to shift these three : medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3 to the place of after 'medcine_preg_oth'.

My idea is shifting the specific columns to place after/ before specific columns in dataframe for wider purpose .
please suggest me!
Thanks

python pandas data-cleaning

share|improve this question

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

0

$begingroup$

In dataframe example :

 medcine_preg_oth medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3
0 Berplex Berplex None None
1 NaN NaN NaN NaN
2 NaN NaN NaN NaN
3 obmin obmin None None
4 NaN NaN NaN NaN

'medcine_preg_oth1' 'medcine_preg_oth2' 'medcine_preg_oth3' ,these three columns are in somewhere of dataframe with other columns.

I want to shift these three : medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3 to the place of after 'medcine_preg_oth'.

My idea is shifting the specific columns to place after/ before specific columns in dataframe for wider purpose .
please suggest me!
Thanks

python pandas data-cleaning

share|improve this question

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

In dataframe example :

 medcine_preg_oth medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3
0 Berplex Berplex None None
1 NaN NaN NaN NaN
2 NaN NaN NaN NaN
3 obmin obmin None None
4 NaN NaN NaN NaN

'medcine_preg_oth1' 'medcine_preg_oth2' 'medcine_preg_oth3' ,these three columns are in somewhere of dataframe with other columns.

I want to shift these three : medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3 to the place of after 'medcine_preg_oth'.

My idea is shifting the specific columns to place after/ before specific columns in dataframe for wider purpose .
please suggest me!
Thanks

python pandas data-cleaning

share|improve this question

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

 medcine_preg_oth medcine_preg_oth1 medcine_preg_oth2 medcine_preg_oth3
0 Berplex Berplex None None
1 NaN NaN NaN NaN
2 NaN NaN NaN NaN
3 obmin obmin None None
4 NaN NaN NaN NaN

share|improve this question

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share|improve this question

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

edited Mar 18 at 7:00

Toros91

1,9942628

edited Mar 18 at 7:00

Toros91

1,9942628

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked Mar 18 at 6:33

Theinzaw Theinzaw

1

2 Answers
2

active

oldest

votes

0

$begingroup$

If I get the question correct, you just need to change the order of your columns. This can be simply done by reassigning the new order of your columns to the dataframe.

For example:

#['a', 'b', 'c'] <-given columns order
df = df[['c', 'b', 'a']]

You can also use the built-in function reindex to accomplish you task as follow:

cols = df.columns.tolist() #['a', 'b', 'c']
new_cols = [['c', 'b', 'a']]
df = df.reindex(columns=new_cols)

EDIT:

If you have a large number of columns, the problem will arise in how you get the new_cols list. To do this you can use list indexing and slicing. Firstly get the index of columns you wnat to replace by using:

df.columns.get_loc("b") #1

Now suppose you have 699 columns and want to place the 100th and 200th column after the 7th one, you can do this:

cols = cols[0:7] + [cols[100]] + [cols[200]] + cols[8:100] + cols[101:200] + cols[201:]

You can now use this column to change the order of your columns in the above mentioned way. The expression will vary depending on your use case.

share|improve this answer

edited Mar 18 at 12:20

answered Mar 18 at 7:15

bkshibkshi

638111

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Hi thanks for your suggestion ,but there are 699 columns in original dataframe , included of these four columns in somewhere of dataframe . So it would take time too!
  $endgroup$
  – Theinzaw
  Mar 18 at 7:39
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  I have edited the answer.
  $endgroup$
  – bkshi
  Mar 18 at 11:40
  

  
  
  
  

add a comment | 

0

$begingroup$

x=df.columns.get_loc('col') # getting column index , the position before that col.

var_list=new_var # list of columns that are wanted to move or shift if the column are
# multiples and also they are in sequence index column.
new_position = x
for var in var_list:
cols = df.columns.tolist()
column_to_move = var
new_position += 1
cols.insert(new_position, cols.pop(cols.index(column_to_move)))
df = df[cols]

share|improve this answer

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

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0

$begingroup$

If I get the question correct, you just need to change the order of your columns. This can be simply done by reassigning the new order of your columns to the dataframe.

For example:

#['a', 'b', 'c'] <-given columns order
df = df[['c', 'b', 'a']]

You can also use the built-in function reindex to accomplish you task as follow:

cols = df.columns.tolist() #['a', 'b', 'c']
new_cols = [['c', 'b', 'a']]
df = df.reindex(columns=new_cols)

EDIT:

If you have a large number of columns, the problem will arise in how you get the new_cols list. To do this you can use list indexing and slicing. Firstly get the index of columns you wnat to replace by using:

df.columns.get_loc("b") #1

Now suppose you have 699 columns and want to place the 100th and 200th column after the 7th one, you can do this:

cols = cols[0:7] + [cols[100]] + [cols[200]] + cols[8:100] + cols[101:200] + cols[201:]

You can now use this column to change the order of your columns in the above mentioned way. The expression will vary depending on your use case.

share|improve this answer

edited Mar 18 at 12:20

answered Mar 18 at 7:15

bkshibkshi

638111

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Hi thanks for your suggestion ,but there are 699 columns in original dataframe , included of these four columns in somewhere of dataframe . So it would take time too!
  $endgroup$
  – Theinzaw
  Mar 18 at 7:39
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  I have edited the answer.
  $endgroup$
  – bkshi
  Mar 18 at 11:40
  

  
  
  
  

add a comment | 

0

$begingroup$

If I get the question correct, you just need to change the order of your columns. This can be simply done by reassigning the new order of your columns to the dataframe.

For example:

#['a', 'b', 'c'] <-given columns order
df = df[['c', 'b', 'a']]

You can also use the built-in function reindex to accomplish you task as follow:

cols = df.columns.tolist() #['a', 'b', 'c']
new_cols = [['c', 'b', 'a']]
df = df.reindex(columns=new_cols)

EDIT:

If you have a large number of columns, the problem will arise in how you get the new_cols list. To do this you can use list indexing and slicing. Firstly get the index of columns you wnat to replace by using:

df.columns.get_loc("b") #1

Now suppose you have 699 columns and want to place the 100th and 200th column after the 7th one, you can do this:

cols = cols[0:7] + [cols[100]] + [cols[200]] + cols[8:100] + cols[101:200] + cols[201:]

You can now use this column to change the order of your columns in the above mentioned way. The expression will vary depending on your use case.

share|improve this answer

edited Mar 18 at 12:20

answered Mar 18 at 7:15

bkshibkshi

638111

$endgroup$

• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  Hi thanks for your suggestion ,but there are 699 columns in original dataframe , included of these four columns in somewhere of dataframe . So it would take time too!
  $endgroup$
  – Theinzaw
  Mar 18 at 7:39
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  $begingroup$
  I have edited the answer.
  $endgroup$
  – bkshi
  Mar 18 at 11:40
  

  
  
  
  

add a comment | 

$begingroup$

If I get the question correct, you just need to change the order of your columns. This can be simply done by reassigning the new order of your columns to the dataframe.

For example:

#['a', 'b', 'c'] <-given columns order
df = df[['c', 'b', 'a']]

You can also use the built-in function reindex to accomplish you task as follow:

cols = df.columns.tolist() #['a', 'b', 'c']
new_cols = [['c', 'b', 'a']]
df = df.reindex(columns=new_cols)

EDIT:

If you have a large number of columns, the problem will arise in how you get the new_cols list. To do this you can use list indexing and slicing. Firstly get the index of columns you wnat to replace by using:

df.columns.get_loc("b") #1

Now suppose you have 699 columns and want to place the 100th and 200th column after the 7th one, you can do this:

cols = cols[0:7] + [cols[100]] + [cols[200]] + cols[8:100] + cols[101:200] + cols[201:]

You can now use this column to change the order of your columns in the above mentioned way. The expression will vary depending on your use case.

share|improve this answer

edited Mar 18 at 12:20

answered Mar 18 at 7:15

bkshibkshi

638111

$endgroup$

#['a', 'b', 'c'] <-given columns order
df = df[['c', 'b', 'a']]

cols = df.columns.tolist() #['a', 'b', 'c']
new_cols = [['c', 'b', 'a']]
df = df.reindex(columns=new_cols)

df.columns.get_loc("b") #1

cols = cols[0:7] + [cols[100]] + [cols[200]] + cols[8:100] + cols[101:200] + cols[201:]

share|improve this answer

edited Mar 18 at 12:20

answered Mar 18 at 7:15

bkshibkshi

638111

answered Mar 18 at 7:15

bkshibkshi

638111

answered Mar 18 at 7:15

bkshibkshi

638111

0

$begingroup$

x=df.columns.get_loc('col') # getting column index , the position before that col.

var_list=new_var # list of columns that are wanted to move or shift if the column are
# multiples and also they are in sequence index column.
new_position = x
for var in var_list:
cols = df.columns.tolist()
column_to_move = var
new_position += 1
cols.insert(new_position, cols.pop(cols.index(column_to_move)))
df = df[cols]

share|improve this answer

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

0

$begingroup$

x=df.columns.get_loc('col') # getting column index , the position before that col.

var_list=new_var # list of columns that are wanted to move or shift if the column are
# multiples and also they are in sequence index column.
new_position = x
for var in var_list:
cols = df.columns.tolist()
column_to_move = var
new_position += 1
cols.insert(new_position, cols.pop(cols.index(column_to_move)))
df = df[cols]

share|improve this answer

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

x=df.columns.get_loc('col') # getting column index , the position before that col.

var_list=new_var # list of columns that are wanted to move or shift if the column are
# multiples and also they are in sequence index column.
new_position = x
for var in var_list:
cols = df.columns.tolist()
column_to_move = var
new_position += 1
cols.insert(new_position, cols.pop(cols.index(column_to_move)))
df = df[cols]

share|improve this answer

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share|improve this answer

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

answered 2 days ago

Theinzaw Theinzaw

1

New contributor

Theinzaw is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

answered 2 days ago

Theinzaw Theinzaw

1